[1]刘 昊.基于GM(1,1)与反向传输神经网络的大学生体育成绩预测[J].南京理工大学学报(自然科学版),2017,41(06):760.[doi:10.14177/j.cnki.32-1397n.2017.41.06.015]
　Liu Hao.Sports performance prediction for college students based onGM(1,1)and back propagation neural network[J].Journal of Nanjing University of Science and Technology,2017,41(06):760.[doi:10.14177/j.cnki.32-1397n.2017.41.06.015]
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基于GM(1,1)与反向传输神经网络的大学生体育成绩预测()
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《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年06期
页码:
760
栏目:
出版日期:
2017-12-31

文章信息/Info

Title:
Sports performance prediction for college students based onGM(1,1)and back propagation neural network
文章编号:
1005-9830(2017)06-0760-05
作者:
刘 昊
中南财经政法大学 体育部,湖北 武汉 430064
Author(s):
Liu Hao
Department of Physical Education,Zhongnan University of Economics and Law,Wuhan 430064,China
关键词:
灰色模型;  反向传输神经网络;  大学生;  体育成绩预测;  组合预测
Keywords:
gray model;  back propagation neural network;  college students;  sports performance prediction;  combined prediction
分类号:
TP183
DOI:
10.14177/j.cnki.32-1397n.2017.41.06.015
摘要:
为了提高预测精度,提出了基于灰色模型GM(1,1)与反向传输神经网络(BPNN)的大学生体育成绩预测方法。采用GM(1,1)对大学生体育成绩的变化趋势进行建模。采用BPNN对GM(1,1)的大学生体育成绩预测结果进行修正。将该文方法应用于中南财经政法大学的男生50 m跑成绩实例中。测试结果表明,该文方法的大学生体育成绩预测精度达到了97.59%。
Abstract:
A sports performance prediction method for college students is proposed based on grey model GM(1,1)and the back propagation neural network(BPNN)to improve the prediction accuracy.The changing trend of sports performance for college students is modeled by the GM(1,1).The predictive results of GM(1,1)are corrected by the BPNN.This method is applied to the 50 meters running performance of students at Zhongnan University of Economics and Law.The test results show that,the sports performance prediction accuracy for college students of the proposed method is 97.59%.

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备注/Memo

备注/Memo:
收稿日期:2017-03-13 修回日期:2017-09-27
基金项目:湖北省高等学校省级教学研究项目(2013160)
作者简介:刘昊(1972-),男,副教授,主要研究方向:体育教育训练理论与体育经济学,E-mail:liuhao126@126.com。
引文格式:刘昊.基于GM(1,1)与反向传输神经网络的大学生体育成绩预测[J].南京理工大学学报,2017,41(6):760-764.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-12-31